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What is the fringe in the context of search algorithms? In English, the fringe is (also) defined as the outer, marginal, or extreme part of an area, group, or sphere of activity In the context of AI search algorithms, the state (or search) space is usually represented as a graph, where nodes are states and the edges are the connections (or actions) between the corresponding states
A* and uniform-cost search are apparently incomplete Stack Exchange Network Stack Exchange network consists of 183 Q A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers
What is the difference between tree search and graph search? There is always a lot of confusion about this concept, because the naming is misleading, given that both tree and graph searches produce a tree (from which you can derive a path) while exploring the search space, which is usually represented as a graph
Why is A* optimal if the heuristic function is admissible? The tree search does not remember which states it has already visited, only the "fringe" of states it hasn't visited yet A graph search is a general search strategy for searching graph-structured problems, where it's possible to double back to an earlier state, like in chess (e g both players can just move their kings back and forth)
ai design - Artificial Intelligence Stack Exchange Stack Exchange Network Stack Exchange network consists of 183 Q A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers
What is the space complexity of breadth-first search? The space complexity of the breadth-first search algorithm is O(bd O (b d) in the worst case, and it corresponds to the largest possible number of nodes that may be stored in the frontier at once, where the frontier is the set of nodes (or states) that you are currently considering for expansion
How is iterative deepening A* better than A*? A* becomes impractical when the search space is huge, because of the memory constraints So, in those cases, IDA* is definitely more appropriate In general, IDA* is one of the very best optimal state space search techniques around However, A* is conceptually simpler than IDA* As a consequence, in practice, A* may be easier to implement than
If an heuristic is not admissible, can it be consistent? I am solving a problem in which, according to the given values, the heuristic is not admissible According to my calculation from other similar problems, it should be consistent, as well as keeping